A NOVEL CONCEPT OF MORPHOLOGY PIVOTAL ELEMENTS FOR OBJECT IMAGE RETRIEVAL
Hiromitsu Hama, Thi Thi Zin, Pyke Tin · 2011
In this paper, we introduce a novel and simple Pivotal Element (PE) con- cept in mathematical morphological operations for object image retrieval schemes based on combinations of empirical and statistical analyses. Mathematical morphology is very attractive for this purpose because it efficiently deals with geometrical features like size, shape, contrast or connectivity that can be considered as image retrieval oriented features. With an optimized structure, morphological dilation is more effective to detect object spot target in image sequences. Based on the real convexgure, morphological operation with circular structure is designed in this paper. The PE is introduced to optimize the noisy background elements. The empirical threshold is decided approximately based on the statistical characters. In this aspect, two approaches for solving morphological applica- tions to image data distributed on the unit circle are presented. In therst approach, a framework for analyzing images, called pivotal role, has been developed based on a set of concentric circles with adjustable radii, with exactly one circle centered at each pivotal image pixel. The second approach is based on Markov decision processes which operate only on grouped data. The retrieval quality is improved by dynamically changing the com- binatorial coefficients that are used in equations of optimality principles. by using it as a priori knowledge of the morphology operation, it does favor to improve the algorithm's accuracy and adaptability. The experiment shows that the new concept of PE has made the morphological operations to achieve a higher retrieval efficiency and accuracy.